Feature selection for text classification with Naïve Bayes

By Jingnian Chen, Houkuan Huang, Shengfeng Tian, Youli Qu. Expert systems with applications, 2009

669 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems

View Paper: https://www.semanticscholar.org/paper/e9cd1d6a25aae329dc3f1268a8998898cca26f58

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Citations in the corpus

Long Document Classification From Local Word Glimpses via Recurrent Attention Learning (2019, methodology): “[20] converted documents to features by two feature selection methods, Multi-class Odds Ratio (MOR) and Class Discriminating Measure (CDM), then fed these features into Naive Bayes for text categorization.”
A Review of Machine Learning Algorithms for Text-Documents Classification (2010, background): “Almost every text domain has much number of features, most of these features are not relevant and beneficial for text classification task, and even some noise features may sharply reduce the classification accuracy [16].”
A Systematic Review on Affective Computing: Emotion Models, Databases, and Recent Advances (2022, background): “[125] 2008 Aspect-level CDM NB Reuters-2157 10 classes: 85.”
A Comparative Analysis of Logistic Regression, Random Forest and KNN Models for the Text Classification (2020, background): “These can directly alter the easy of application by transforming the commands that we speak, into direct actions by machines [10].”
SourceFinder: Finding Malware Source-Code from Publicly Available Repositories (2020, background): “We want to identify the most discerning words from each text field, which is a standard process in NLP for improving the scalability, efficiency and accuracy of a text classifier [12].”
Text mining of news-headlines for FOREX market prediction: A Multi-layer Dimension Reduction Algorithm with semantics and sentiment (2015, methodology): “Frequency of the n-gram in one profile Schumaker and Chen (2009) Bag of Words, noun phrases, named entities Minimum occurrence per document Binary Li (2010) Bag-of-Words, tone and content Pre-defined dictionaries Binary, Dictionary value Huang et al. (2010) Simultaneous terms, ordered pairs…”